Zobrazeno 1 - 10
of 15 609
pro vyhledávání: '"A. Krishnakumar"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023)
Abstract All landscapes, including estuarine islands, normally try to restore their geomorphic isostasy in all anthropogenic interventions on land dynamics. Munroe Island has been experiencing drastic environmental degradation, such as land subsidenc
Externí odkaz:
https://doaj.org/article/15e7680d0a7b4f3b8952fb598f351bca
Autor:
Flöther, Frederik F., Blankenberg, Daniel, Demidik, Maria, Jansen, Karl, Krishnakumar, Rajiv, Laanait, Nouamane, Parida, Laxmi, Saab, Carl, Utro, Filippo
Biomarkers play a central role in medicine's gradual progress towards proactive, personalized precision diagnostics and interventions. However, finding biomarkers that provide very early indicators of a change in health status, particularly for multi
Externí odkaz:
http://arxiv.org/abs/2411.10511
Models based on recursive adaptive partitioning such as decision trees and their ensembles are popular for high-dimensional regression as they can potentially avoid the curse of dimensionality. Because empirical risk minimization (ERM) is computation
Externí odkaz:
http://arxiv.org/abs/2411.04394
Autor:
Joshi, N., Mahendrakar, Vaibhav, Niranjan, M., Yadav, Raghuveer Singh, Krishnakumar, E, Pandey, A., Vexiau, R, Dulieu, O., Rangwala, S. A.
The formation of Li$_2^+$ and subsequently Li$^+$ ions, during the excitation of $^7$Li atoms to the $3S_{1/2}$ state in a $^7$Li magneto optical trap (MOT), is probed in an ion-atom hybrid trap. Associative ionization occurs during the collision of
Externí odkaz:
http://arxiv.org/abs/2411.01209
Autor:
Iraci, F., Chalumeau, A., Tiburzi, C., Verbiest, J. P. W., Possenti, A., Shaifullah, G. M., Susarla, S. C., Krishnakumar, M. A., Lam, M. T., Cromartie, H. T., Kerr, M., Grießmeier, Jean-Mathias
Radio pulsars allow the study of the ionised interstellar medium and its dispersive effects, a major noise source in gravitational wave searches using pulsars. In this paper, we compare the functionality and reliability of three commonly used schemes
Externí odkaz:
http://arxiv.org/abs/2410.22170
We theoretically investigate the in-context learning capabilities of transformers in the context of learning mixtures of linear regression models. For the case of two mixtures, we demonstrate the existence of transformers that can achieve an accuracy
Externí odkaz:
http://arxiv.org/abs/2410.14183
Autor:
Touzel, Maximilian Puelma, Sarangi, Sneheel, Welch, Austin, Krishnakumar, Gayatri, Zhao, Dan, Yang, Zachary, Yu, Hao, Kosak-Hine, Ethan, Gibbs, Tom, Musulan, Andreea, Thibault, Camille, Gurbuz, Busra Tugce, Rabbany, Reihaneh, Godbout, Jean-François, Pelrine, Kellin
The rise of AI-driven manipulation poses significant risks to societal trust and democratic processes. Yet, studying these effects in real-world settings at scale is ethically and logistically impractical, highlighting a need for simulation tools tha
Externí odkaz:
http://arxiv.org/abs/2410.13915
We explore the capability of transformers to address endogeneity in in-context linear regression. Our main finding is that transformers inherently possess a mechanism to handle endogeneity effectively using instrumental variables (IV). First, we demo
Externí odkaz:
http://arxiv.org/abs/2410.01265
Autor:
Huo, Pingyi, Devulapally, Anusha, Maruf, Hasan Al, Park, Minseo, Nair, Krishnakumar, Arunachalam, Meena, Akbulut, Gulsum Gudukbay, Kandemir, Mahmut Taylan, Narayanan, Vijaykrishnan
Deep Learning Recommendation Models (DLRMs) have become increasingly popular and prevalent in today's datacenters, consuming most of the AI inference cycles. The performance of DLRMs is heavily influenced by available bandwidth due to their large vec
Externí odkaz:
http://arxiv.org/abs/2409.16633
Autor:
Susarla, S. C., Chalumeau, A., Tiburzi, C., Keane, E. F., Verbiest, J. P. W., Hazboun, J. S., Krishnakumar, M. A., Iraci, F., Shaifullah, G. M., Golden, A., Nielsen, A. S. Bak, Donner, J., Grießmeier, J. M., Keith, M. J., Osłowski, S., Porayko, N. K., Serylak, M., Anderson, J. M., Brüggen, M., Ciardi, B., Dettmar, R. J., Hoeft, M., Künsemöller, J., Schwarz, D., Vocks, C.
High-precision pulsar timing is highly dependent on precise and accurate modeling of any effects that impact the data. It was shown that commonly used Solar Wind models do not accurately account for variability in the amplitude of the Solar wind on b
Externí odkaz:
http://arxiv.org/abs/2409.09838